Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Marina Riabiz"'
Publikováno v:
Annual Review of Statistics and Its Application. 9:529-555
Markov chain Monte Carlo (MCMC) is the engine of modern Bayesian statistics, being used to approximate the posterior and derived quantities of interest. Despite this, the issue of how the output from a Markov chain is post-processed and reported is o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9e5a6a6f662492ec96a103cc4c2bf3c
https://doi.org/10.1146/annurev-statistics-040220-091727
https://doi.org/10.1146/annurev-statistics-040220-091727
Publikováno v:
Journal of Molecular and Cellular Cardiology. 173:148-149
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa71b1beef547d80b7a87fde926952ce
https://doi.org/10.1016/j.yjmcc.2022.08.291
https://doi.org/10.1016/j.yjmcc.2022.08.291
Autor:
Elizabeth M. Cherry, Pras Pathmanathan, Chris D. Cantwell, Gernot Plank, Steven A. Niederer, Flavio H. Fenton, Marina Riabiz, Yasser Aboelkassem, Tammo Delhaas, Linwei Wang, Cesare Corrado, R. W. dos Santos, Sam Coveney, Caroline H. Roney, Alexander V. Panfilov
Publikováno v:
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
Patient-specific cardiac models are now being used to guide therapies. The increased use of patient-specific cardiac simulations in clinical care will give rise to the development of virtual cohorts of cardiac models. These cohorts will allow cardiac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8839364874bcae67c706e9bd96a5ba4
http://hdl.handle.net/10044/1/79532
http://hdl.handle.net/10044/1/79532
Autor:
Marina Riabiz, Wilson Ye Chen, Jon Cockayne, Pawel Swietach, Steven A. Niederer, Lester Mackey, Chris. J. Oates
Publikováno v:
Riabiz, M, Chen, W Y, Cockayne, J, Swietach, P, Niederer, S, Mackey, L & Oates, C 2021, ' Optimal thinning of MCMC output ', Journal of the Royal Statistical Society. Series B: Statistical Methodology .
The use of heuristics to assess the convergence and compress the output of Markov chain Monte Carlo can be sub-optimal in terms of the empirical approximations that are produced. Typically a number of the initial states are attributed to "burn in" an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad8de3ac4e55c0ab97de8786427f1c6d
Autor:
Chon Lok Lei, Kylie A. Beattie, Alexander V. Panfilov, Chris D. Cantwell, Rodrigo Weber dos Santos, Yasser Aboelkassem, Dominic G. Whittaker, John Walmsley, Sanmitra Ghosh, Charles Houston, Gary R. Mirams, Tammo Delhaas, Pras Pathmanathan, Gustavo Montes Novaes, Marina Riabiz, Keith Worden, Richard D. Wilkinson
Publikováno v:
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propaga
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d0d2041d046b643a3c04174c846a7dd
Publikováno v:
ACSSC
In this paper we introduce a new class of state space models based on shot-noise simulation representations of nonGaussian Levy-driven linear systems, represented as stochastic differential equations. In particular a conditionally Gaussian version of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f1cd92784638585754bb2143b1d1d89
https://doi.org/10.1109/ieeeconf44664.2019.9048715
https://doi.org/10.1109/ieeeconf44664.2019.9048715
Publikováno v:
CAMSAP
© 2017 IEEE. We report the results of a series of numerical studies examining the convergence rate for some approximate representations of α-stable distributions, which are a highly intractable class of distributions for inference purposes. Our pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85c36ee9797d6fc3bc98aa72c8c59a9a
Publikováno v:
ISIT
We report the results of several theoretical studies into the convergence rate for certain random series representations of $\alpha$ -stable random variables, which are motivated by and find application in modelling heavy-tailed noise in time series
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adb4b6320a8bd83b86245e369158fabc
https://doi.org/10.1109/isit.2018.8437513
https://doi.org/10.1109/isit.2018.8437513
The results of a series of theoretical studies are reported, examining the convergence rate for different approximate representations of $\alpha$-stable distributions. Although they play a key role in modelling random processes with jumps and discont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45bfbd0ca5ad5b5102a4d7a40cced20f
http://arxiv.org/abs/1802.10065
http://arxiv.org/abs/1802.10065
Publikováno v:
Digital Signal Processing. 47:96-115
In this paper we develop an approach to Bayesian Monte Carlo inference for skewed α-stable distributions. Based on a series representation of the stable law in terms of infinite summations of random Poisson process arrival times, our framework leads
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b9fce5c53cee3d73e2a999604f70d60
https://doi.org/10.1016/j.dsp.2015.08.018
https://doi.org/10.1016/j.dsp.2015.08.018